code: def prepare_config_and_inputs(self):
      input_ids = ids_tensor(
          [self.batch_size, self.seq_length], self.vocab_size
      )
  
      attention_mask = None
      if self.use_attention_mask:
          attention_mask = random_attention_mask(
              [self.batch_size, self.seq_length]
          )
  
      token_type_ids = None
      if self.use_token_type_ids:
          token_type_ids = ids_tensor(
              [self.batch_size, self.seq_length], self.type_vocab_size
          )
  
      config = AlbertConfig(
          vocab_size=self.vocab_size,
          hidden_size=self.hidden_size,
          num_hidden_layers=self.num_hidden_layers,
          num_attention_heads=self.num_attention_heads,
          intermediate_size=self.intermediate_size,
          hidden_act=self.hidden_act,
          hidden_dropout_prob=self.hidden_dropout_prob,
          attention_probs_dropout_prob=self.attention_probs_dropout_prob,
          max_position_embeddings=self.max_position_embeddings,
          type_vocab_size=self.type_vocab_size,
          is_decoder=False,
          initializer_range=self.initializer_range,
      )
  
      return config, input_ids, token_type_ids, attention_mask
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/models/albert/test_modeling_flax_albert.py
imports: import unittest
  import numpy
  from transformers import AlbertConfig, is_flax_available
  from transformers.testing_utils import require_flax, slow
  from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 2 for calling the FlaxAlbertModelTester obj's underlying member method code with example usage: obj.prepare_config_and_inputs() and returns: config,  input_ids,  token_type_ids,  attention_mask